Yunhao (Andy) Ge
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I am a Ph.D. Candidate in the CS Department at University of Southern California, advised by Prof. Laurent Itti. I am also a Visiting Student Researcher at Stanford Vision and Learning (SVL) Lab advised by Prof. Jiajun Wu. I'm interested in Machine Learning, Computer vision, and their applications towards Trustworthy, Human-like AI and Data-centric AI. My current research focuses include:
Research opportunities: I am happy to collaboration. If you are interested, please send me an email. I especially encourage USC master/undergraduate students who want to involve exciting projects targeting top-tier conferences/journals to reach out.
[2022/12/01] Starting a new journey at Stanford Vision and Learning (SVL) Lab as a Visiting Student Researcher, advised by Prof. Jiajun Wu.
[2022/08/16] I was awarded the Amazon ML Fellowship (2022-2023), and will be an Amazon Fellow at USC + Amazon Center on Secure & Trusted Machine Learning. Thank you Amazon!
[2022/08/16] One paper on Disentangled and Convex Representation learning is accepted by WACV 2023, code is coming soon.
[2022/07/03] Two papers on NeRF and Humanoid Neural Network are accepted by ECCV 2022, code are released.
[2022/05/31] I will be joining Google Research as a student researcher, advised by Dr. Jiaping Zhao , Dr. Jie Ren , Dr. Balaji Lakshminarayanan and Prof. Ming-Hsuan Yang.
[2022/01/20] Finally passed my qual exam and officially became a PhD Candidate now.
[2021/08/23] I will be joining Google Cloud AI as a student researcher, advised by Dr. Sercan Arik and Dr. Jinsung Yoon
[2021/07/15] USC News , Tech Xplore , Technology Networks and other media pressed our ICLR 2021 paper: Group-Supervised Learning (Enabling the 'imagination' of artificial intelligence)
[2021/05/17] I will be joining Computer Vision Group at Microsoft Research Redmond as a research intern in summer 2021, advised by Dr. Vibhav Vineet and Dr. Neel Joshi
[2021/04/07] Releasing Img2SceneGraph, a pipeline that transfers images to scene graphs with node attributes! Welcome to Download and try!
[2021/04/02] One paper (Graph Autoencoder for Graph Compression and Representation Learning) was accepted by Neural Compression Workshop @ICLR 2021 as Spotlight!
[2021/02/28] One paper (A Peek Into the Reasoning of Neural Networks: Interpreting with Structural Visual Concepts) was accepted by CVPR 2021!
[2021/01/16] One paper (Beneficial Perturbation Network for designing general adaptive artificial intelligence systems) was accepted by TNNLS!
[2021/01/12] One paper (Zero-shot Synthesis with Group-Supervised Learning) was accepted by ICLR 2021!
[2020/09/14] Fonts dataset was proposed for fast testing and idea iteration on disentangled representation learning and zero-shot synthesis. Welcome to Download and try!
[2020/07/02] One paper (Pose Augmentation: Class-agnostic Object Pose Transformation) was accepted by ECCV 2020!
[2020/05/12] I will be joining UII America as a research intern in summer 2020, advised by Dr. Ziyan Wu and Dr. Srikrishna Karanam
[2019/08/12] I will be joining USC CS Ph.D. Program in fall 2019, advised by Prof. Laurent Itti.
[2019/07/01] One paper (Synthesis and inpainting-based MR-CT registration) was accepted by MICCAI 2019.
[2019/03/01] One paper (Unpaired Whole-Body Mr to CT Synthesis) was accepted by ISBI 2019.
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DALL-E for Detection: Language-driven Compositional Image Synthesis for Object Detection Yunhao Ge*, Jiashu Xu*, Brian Nlong Zhao, Laurent Itti, Vibhav Vineet (*=equal contribution) arXiv:2206.09592, 2022. [paper] |
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EM-Paste: EM-guided Cut-Paste with DALL-E Augmentation for Image-level Weakly Supervised Instance Segmentation Yunhao Ge*, Jiashu Xu*, Brian Nlong Zhao, Laurent Itti, Vibhav Vineet (*=equal contribution) arXiv:2212.07629, 2022. [paper] |
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Invariant Structure Learning for Better Generalization and Causal Explainability Yunhao Ge, Sercan Ö. Arik, Jinsung Yoon, Ao Xu, Laurent Itti and Tomas Pfister arXiv:2206.06469, 2022. [paper] |
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Improving Zero-shot Generalization and Robustness of Multi-modal Models Yunhao Ge*,Jie Ren*, Yuxiao Wang, Andrew Gallagher, Ming-Hsuan Yang, Laurent Itti, Hartwig Adam, Balaji Lakshminarayanan, and Jiaping Zhao (*=equal contribution) NeurIPS 2022 Workshop (ML Safety Workshop ). [paper] |
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Neural-Sim: Learning to Generate Training Data with NeRF Yunhao Ge, Harkirat Behl*, Jiashu Xu*, Suriya Gunasekar, Neel Joshi, Yale Song, Xin Wang, Laurent Itti, and Vibhav Vineet (*=equal contribution as second author) ECCV 2022 (European Conference on Computer Vision ). |
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Contributions of Shape, Texture, and Color in Visual Recognition Yunhao Ge*, Yao Xiao*, Zhi Xu, Xingrui Wang, Laurent Itti (*=equal contribution) ECCV 2022 (European Conference on Computer Vision ). |
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A Peek Into the Reasoning of Neural Networks: Interpreting with Structural Visual Concepts Yunhao Ge, Yao Xiao, Zhi Xu, Meng Zheng, Srikrishna Karanam, Terrence Chen, Laurent Itti and Ziyan Wu CVPR 2021 (IEEE/ CVF International Conference on Computer Vision and Pattern Recognition ). |
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Zero-shot Synthesis with Group-Supervised Learning Yunhao Ge, Sami Abu-El-Haija, Gan Xin and Laurent Itti ICLR 2021 (International Conference on Learning Representations). [paper]
[code]
[website]
[Fonts Dataset]
[USC Viterbi Press]
[知乎]
[AI科技评论] |
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Encouraging Disentangled and Convex Representation with Controllable Interpolation Regularization Yunhao Ge, Zhi Xu, Yao Xiao, Gan Xin, Yunkui Pang and Laurent Itti WACV 2023 (IEEE/CVF Winter Conference on Applications of Computer Vision). [paper] |
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Graph Autoencoder for Graph Compression and Representation Learning Yunhao Ge*, Yunkui Pang*, Linwei Li and Laurent Itti (*=equal contribution) ICLR 2021 Workshop (Neural Compression: From Information Theory to Applications--Workshop@ ). [paper] [code] [Img2SceneGraph] Spotlight Presentation |
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Pose Augmentation: Class-agnostic Object Pose Transformation for Object Recognition Yunhao Ge, Jiaping Zhao, Laurent Itti ECCV 2020 (European Conference on Computer Vision). [paper] [github] [video-1min] [video-10min] |
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Beneficial Perturbation Network for designing general adaptive artificial intelligence systems Shixian Wen, Amanda Rios*, Yunhao Ge* and Laurent Itti (*=equal contribution as second author) TNNLS 2021 ( IEEE Transactions on Neural Networks and Learning Systems ). [paper] |
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Unpaired MR to CT Synthesis with Explicit Structural Constrained Adversarial Learning Yunhao Ge*, Dongming Wei*, Zhong Xue, Yiqiang Zhan, Xiang Zhou, Qian Wang and Shu Liao (*=equal contribution) ISBI 2019 (IEEE International Symposium on Biomedical Imaging). |
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Synthesis and inpainting-based MR-CT registration for image-guided thermal ablation of liver tumors Dongming Wei, Sahar Ahmad, Jiayu Huo, Wen Peng, Yunhao Ge, Zhong Xue, Pew-Thian Yap, Wentao Li, Dinggang Shen, Qian Wang MICCAI 2019 (International Conference on Medical Image Computing and Computer-Assisted Intervention). [paper] |
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Unpaired Whole-body MR to CT Synthesis with Correlation Coefficient Constrained Adversarial Learning Yunhao Ge, Zhong Xue, Yiqiang Zhan, Xiang Zhou and Shu Liao SPIE 2019 (SPIE-Medical Imaging). Oral Presentation |
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Systems and methods for image processing S Liao, GE Yunhao, WEI Dongming US Patent App. 16/729,303. |
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Pulmonary Nodular Assisted Detection System Based on AI(V1.0) Bin Li, Yunhao Ge 2018SR037095. |
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A Two-Layer Barrier Free Parking Equipment Based on Bionic Manipulator Yunhao Ge, Shangze Yang, Zheng Zhang, Weixin Yan and Yanzheng Zhao CN201610712048. |
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A Double Decker Parking Equipment based on Shear Lifting Mechanism and Hydraulic Mechanism Yunhao Ge, Xulong Zhou, Peng Liu and Yanzheng Zhao CN201610704408. |
Last update: Jan. 20, 2023